Ask The Analyst: As finance teams scrutinize AI token budgets, how should HR leaders fight for and defend their allocations – and what happens if they can't?

Every week for The Briefing, UNLEASH’s weekly intelligence email for senior decision-makers, we put the tough questions to the true HR experts: Our community of analysts.

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This week’s question: As finance teams scrutinize AI token budgets, how should HR leaders fight for and defend their allocations – and what happens if they can't?

Here are the thoughts of the HR analyst community:

Jean-Baptiste Audrerie, Co-Founder, NexaRH

Stop defending AI as an experiment. Defend it as intelligence infrastructure. The shift from per-user subscriptions to pay-per-task pricing means every AI agent action burns tokens.

Welcome to Tokenmaxxing: optimizing consumption is now a financial discipline, not a technical afterthought. HR is seen as back-office. Finance will always prioritize revenue-generating functions first.

To survive the budget fight, HR leaders must prove ROI on high-volume, rule-based processes, and explicit tasks: compliance checks, workforce analytics, forecasting, scenario modelling, workforce design. These are domains where AI delivers the highest return because data volume is high, rules are clear, and human risk is low.

But maturity means being selective. AI analyzes and simulates. Leaders decide. When decisions directly impact people or shape the organization we want to build, AI informs, it does not decide.

The real unlock is not the prompt. It is chaining tasks: AI's biggest impact comes from how it reshapes entire workflows, how tasks are sequenced, grouped, and handed off between humans and machines. If HR cannot articulate this, budgets will flow elsewhere. The function will remain trapped between a System of Record and the promise of a System of Insights, while employees quietly fund their own productivity gains through Shadow AI, paying out of pocket for tools the organization refuses to invest in.

Rebecca Wettemann, CEO & Principal Analyst, Valoir

Getting budget for AI tokens is less about defending an allocation and more about building a solid business case. HR leaders should recognize that there will be at least two other competitors for their token budget: other departments like sales and marketing, and other agentic platform and app providers.

This means they need to be able to make the case beyond the walls of HR, both justifying the business benefits of their HR AI spend and showing that their chosen technology approach is more cost effective and less risky than competing approaches. This means building clear and concise business cases that credibly tie AI token use to top-line or bottom-line improvements and having enough technology literacy to articulate why their choice of HR AI solutions is the best tool for the job.

Without a solid business case, HR leaders will see their AI projects prioritized below other departments,’ and will have less control over where, ultimately, HR-related workflows will live.

Era Singh, Practice Director, Everest Group

HR leaders should defend AI token allocations by shifting the conversation from “usage cost” to “workforce impact.” The strongest case is not that HR needs more AI access, but that AI is becoming core infrastructure for employee experience, manager productivity, HR service delivery, learning, recruiting, and workforce intelligence.

To fight for their share, HR leaders need to quantify where tokens create measurable value: fewer HR tickets, faster resolution times, improved self-service, reduced recruiter workload, better manager support, faster policy interpretation, and higher employee adoption of digital HR channels.

They should also segment AI usage by business-criticality, ensuring that high-value use cases such as employee support, compliance-sensitive guidance, talent acquisition, and workforce planning are prioritized over experimentation.

The real question finance and HR should ask together is not “How do we reduce token consumption?” but “Which AI interactions are worth paying for, and how do we govern them intelligently?” HR leaders who can answer that with data, prioritization, and clear business outcomes will be far better positioned to defend their allocations.

Josh Bersin, CEO and Founder, The Josh Bersin Company

As finance scrutinizes AI budgets, HR leaders should make sure there are clearly defined HR AI projects, with a business case, that are scoped, prioritized, and ready to start.

The top highest-ROI use cases today fall into five areas: reducing speed and time to hire, employee chatbots and employee self-service for routine transactions, L&D transformation and cost reduction, digital support for HR business partners, and AI agents to speed and simplify performance management and career planning.

In other words, the HR AI business case should not simply be focused on experimentation but refining ideas into clear executable projects. In most cases these AI-fueled projects will include data integration, selected vendor solutions, and a team of HR professionals who are equipped to drive adoption and outcomes.

The days of experimentation and hackathons are not at an end. However, as AI token costs go up, it’s now time to define high-ROI projects that directly contribute to revenue growth, employee retention, or clearly defined cost reduction.

That may not mean simply upgrading the HCM to access lots of new features unless those capabilities have clear and demonstrable ROI.